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https://github.com/adarshgurazada/voice-assistant-using-gemini
Gemini Chatbot
https://github.com/adarshgurazada/voice-assistant-using-gemini
azure azurecognitiveservice gemini-api porcupine wakeword
Last synced: 9 days ago
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Gemini Chatbot
- Host: GitHub
- URL: https://github.com/adarshgurazada/voice-assistant-using-gemini
- Owner: Adarshgurazada
- Created: 2024-06-25T06:02:36.000Z (5 months ago)
- Default Branch: master
- Last Pushed: 2024-10-24T05:20:43.000Z (22 days ago)
- Last Synced: 2024-10-24T23:16:27.378Z (21 days ago)
- Topics: azure, azurecognitiveservice, gemini-api, porcupine, wakeword
- Language: Python
- Homepage:
- Size: 9.77 KB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Voice Assistant Using GEMINI Pro LLM
## Overview
This project showcases a voice assistant powered by the GEMINI Pro LLM, Azure Cognitive Services, and Porcupine wake word detection. The assistant listens for a specific wake word ("Jarvis") and responds to user queries with accurate and contextually appropriate answers. This system is designed for deployment on a rover bot used to scout around industrial areas and perform tasks with precision.
## Features
- **Wake Word Detection**: Utilizes Porcupine for detecting the wake word "Jarvis".
- **Speech Recognition**: Converts spoken language into text using Azure Cognitive Services.
- **Text Generation**: Generates responses using Google's GEMINI Pro LLM.
- **Speech Synthesis**: Converts text responses back to speech using Azure Cognitive Services.
- **Safety Filters**: Includes safety settings to block harmful content categories.
## Setup
### Prerequisites
- Python 3.7 or higher
- [Porcupine](https://picovoice.ai/platform/porcupine/) access key
- Azure Cognitive Services subscription key
- Google GEMINI Pro API key
### Installation
1. Clone the repository:
```bash
git clone https://github.com/Adarshgurazada/Voice-Assistant-Using-GEMINI.git
cd Voice-Assistant-Using-GEMINI
```
2. Install the required Python packages:
```bash
pip install -r requirements.txt
```
3. Create a `.env` file in the root directory and add your API keys:
```env
PORCUPINE=your_porcupine_key
AZURE=your_azure_key
GOOGLE_API=your_google_api_key
```
## Usage
1. Run the main script:
```bash
python main.py
```
2. The assistant will listen for the wake word "Jarvis". Once detected, it will prompt you to ask a question.
3. Speak your query, and the assistant will process it, generate a response, and speak it back to you.
## Code Explanation
### Importing Libraries
- **pyaudio**: For audio input and output.
- **pvporcupine**: For wake word detection.
- **azure.cognitiveservices.speech**: For speech recognition and synthesis.
- **google.generativeai**: For text generation using GEMINI Pro LLM.
- **dotenv**: For loading environment variables.
### Initializing Services
- **Porcupine**: Configured to detect the wake word "Jarvis".
- **Azure Cognitive Services**: Configured for both speech recognition and synthesis.
- **GEMINI Pro LLM**: Configured with generation and safety settings.
### Main Loop
- Continuously listens for the wake word using Porcupine.
- Upon detecting the wake word, prompts the user for a query.
- Converts the user's spoken query to text.
- Sends the text to GEMINI Pro for a response.
- Converts the generated response back to speech and plays it.
## Contributing
1. Fork the repository.
2. Create a new branch (`git checkout -b feature-branch`).
3. Make your changes.
4. Commit your changes (`git commit -m 'Add new feature'`).
5. Push to the branch (`git push origin feature-branch`).
6. Open a pull request.
## Contact
For any inquiries or feedback, please reach out to [[email protected]].